Abstract:- This session will explore how DC/OS and Mesos are being used at Esri to establish a foundational operating environment to enable the consumption of high velocity IoT data using Apache Kafka, streaming analytics using Apache Spark, high-volume storage and querying of spatiotemporal data using Elasticsearch, and recurring batch analytics using Apache Spark & Metronome. Additionally, Esri will share their experience in making their application for DC/OS portable so that it can easily be deployed amongst public cloud providers (Microsoft Azure, Amazon EC2), private cloud providers and on-premise environments. Demonstrations of will be performed throughout the presentation to cement these concepts for the attendees. All demos will be available on a public github repo.

1. Enabling Scalable IoT Applications
Adam Mollenkopf
Real-Time & Big Data GIS Capability Lead, Esri
amollenkopf@esri.com
@amollenkopf

2. Agenda
Emergence of a new class of problem = IoT
Massive scale approach
Deployment portability
1
2
3

3. Creators of Geographic Information System (GIS) software
Esri Overview
• Environmental Systems Research Institute (Esri) was founded in 1969
• Esri develops commercial GIS software called ArcGIS
• Global company with over 350,000 user organizations worldwide
Headquarters in Redlands, CA 80 Esri distributors worldwide

4. 1
Emergence of a new class
of problem = IoT

5. Public Safety
police fire
surveillance
Public Health
hospitals ambulances
Transit
buses taxis rail
trains crowds
Connected Cars
autonomous driving traffic conditions holes
parking meters road conditions slippery areas
network improvements
Energy Usage
electricity gas smart meters
City Workers
sanitation snow plows
Airports
flight status queues
plane location runway status
Buildings
lighting hvac
occupancy counts
Internet of your Things
Environment
noise co2 nitrates
gases temperature humidity
atmospheric pressure radiation
pesticides electromagnetic feedback
rain gauges water level gauges
water quality air quality
Weather
warnings earthquakes
precipitation icy conditions
People
health monitoring
social activity
Telecommunications
cell phone signals dropped calls
bringing geospatial insights to your IoT
IoT & Geospatial
DesktopWeb Device
with Real-Time & Big Data GIS
ArcGIS Enterprise

6. Blueprint
for IoT solutions
Sensors
Actuators
Devices
(or Things)
Environment
IoT PlatformEdge Enterprise
Ingestion
Streaming
Analytics
Data Store
Batch
Analytics
Actions &
Intelligence
Policy & Orchestration
• An IoT platform consists of the following capabilities:
- Ingestion
- Streaming Analytics & Policies
- Actions (including actuation)
- Data Store
- Device Management
- Batch Analytics
- Management Console
- Visualization
- Dashboards
Device
Management
ingestion
analytics
policies & orchestration
management console
data store analytics
visualization
dashboardsactions

7. Sensors
Actuators
Devices
(or Things)
Environment
IoT PlatformEdge Enterprise
Ingestion
Streaming
Analytics
Data Store
Batch
Analytics
Actions &
Intelligence
Policy & Orchestration
Device
Management
ArcGIS
Enterprise
GeoEvent
Server
ingestion
GeoAnalytics
Server
spatiotemporal
big data store
actions
analytics
policies & orchestration
management console
data store analytics
visualization
Operations Dashboard for ArcGIS
Insights for ArcGIS
Esri Story Maps
ArcGIS Earth
ArcGIS Online
ArcGIS Pro
Collector for ArcGIS
Web AppBuilder for ArcGIS
AppStudio for ArcGIS
dashboards
Esri ArcGIS as an IoT Platform
enabling geospatial insights with your IoT solution
• An Esri ArcGIS based IoT platform consists of the following capabilities:
- Ingestion: GeoEvent server input connectors
- Streaming Analytics & Policies: GeoEvent Services
- Actions (including actuation): GeoEvent output connectors
- Data Store: spatiotemporal big data store
- Device Management: for those requiring this functionality another IoT platform can be complemented with Esri ArcGIS.
- Batch Analytics: GeoAnalytics Server
- Management Console: Portal & GeoEvent Manager
- Visualization: Map & Feature Services
- Dashboards: Operations Dashboard, Insights, Story Maps
https://github.com/Esri/integrating-iot-arcgis

8. Edge Enterprise
Ingestion
Streaming
Analytics
Data Store
Batch
Analytics
Actions &
Intelligence
Policy & Orchestration
Device
Management
ArcGIS
Enterprise
GeoEvent
Server
GeoAnalytics
Server
spatiotemporal
big data store
policies & orchestration
management console
data store
visualization
Operations Dashboard for ArcGIS
Insights for ArcGIS
Esri Story Maps
ArcGIS Earth
ArcGIS Online
ArcGIS Pro
Collector for ArcGIS
Web AppBuilder for ArcGIS
AppStudio for ArcGIS
dashboards
Complementing an IoT platform with Esri ArcGIS
enabling geospatial insights with your IoT solution
• The Edge of an IoT broadcasts into an IoT platform such as: Azure IoT, Amazon IoT, Cisco IoT, IBM Bluemix, …
• The IoT platform integrates with Esri ArcGIS to expand it’s capabilities with spatiotemporal analytics,
visualization & dashboards.
Sensors
Actuators
Devices
(or Things)
Gateways
Environment
IoT Platform
ingestion
streaming
analytics
batch
analytics
actions
ingestion
actions
https://github.com/Esri/integrating-iot-arcgis

9. Edge Enterprise
Ingestion Actions &
Intelligence
Policy & Orchestration
Device
Management
Spatiotemporal
Capabilities
visualization
Operations Dashboard for ArcGIS
Insights for ArcGIS
Esri Story Maps
ArcGIS Earth
ArcGIS Online
ArcGIS Pro
Collector for ArcGIS
Web AppBuilder for ArcGIS
AppStudio for ArcGIS
dashboards
Complementing an IoT platform with Esri ArcGIS
enabling geospatial insights with your IoT solution
Sensors
Actuators
Devices
(or Things)
Gateways
Environment
IoT Platform
ingestion
streaming
analytics
data store batch
analytics
• The Edge of an IoT broadcasts into an IoT platform such as: Azure IoT, Amazon IoT, Cisco IoT, IBM Bluemix, …
• The IoT platform integrates with Esri ArcGIS to expand it’s capabilities with spatiotemporal analytics,
visualization & dashboards.
actions
ingestion
actions
https://github.com/Esri/integrating-iot-arcgis

10. Esri ArcGIS as an IoT Platform
enabling geospatial insights with your IoT solution
ArcGIS
Enterprise
ArcGIS
Enterprise
spatiotemporal
big data store
GeoAnalytics
Server
IoT Big Data
GeoEvent
Server
gatewaygateway gateway

11. ArcGIS
Enterprise
ArcGIS
Enterprise
spatiotemporal
big data store
GeoAnalytics
Server
7 86 10 119
Esri ArcGIS as an IoT Platform
enabling geospatial insights with your IoT solution
IoT Big Data
GeoEvent
Server
gatewaygateway gateway
3 4 5
functional servers & spatiotemporal big data store
SHOULD BE on ISOLATED machines!!!
RECOMMENDED environment
11 machines for a
scaled-out & resilient deployment 1
2

12. ArcGIS
Enterprise
enabling geospatial insights with your IoT solution
• A new class of customer is demanding MASSIVE real-time & big data analytic capabilities.
Esri ArcGIS as an IoT Platform
big data analytics & storageingestion & real-time analytics
Big DataIoT
NEEDED environment
10s to 1,000s of machines

13. 2 Massive scale approach

15. =

16. =

17. =

18. +
project Trinity

19. project Trinity
ArcGIS
Enterprise
storage
visualization
GeoEvent
Server
GeoAnalytics
Server
spatiotemporal
big data store

20. enabling geospatial insights with your IoT solution
Esri ArcGIS as an IoT Platform
visualizeingest
storeanalyze
up to thousands e/s up to millions
up to millionsup to thousands e/s

21. MASSIVE real-time & big data GIS capabilities
project Trinity
visualizeingest
storeanalyze
ArcGIS
Enterprise
container
ization
into Microservices
up to thousands e/s up to millions
up to millionsup to thousands e/s
up to billionsup to millions e/s
up to millions e/s up to billions

22. project Trinity
ArcGIS
Enterprise
storage
visualization
GeoEvent
Server
GeoAnalytics
Server
spatiotemporal
big data store

23. project Trinity
ArcGIS Enterprise
storage
visualization

24. project Trinity
containerized microServices
Spatiotemporal
store
Batch
analytic
ArcGIS
Enterprise
monitor admin
Source
ingestion
Gateway Real-Time
analytic
Trinity
mgmt console
monitor admin
Map
service

25. 480 cores, 1.6TB ram, 30TB storage
monitor admin
Trinity
mgmt console
monitor admin
Map
service
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
1 1 11 1 2 2 3 4 3 65 7
1 1 1 1 1 12 2 2 3 4
project Trinity
Trinity ArcGIS
Enterprise
DC/OS with containerized microServices
Source
ingestion
Gateway Real-Time
analytic
Spatiotemporal
store
Batch
analytic

26. 3 Deployment Portability

27. Microsoft Azure
Amazon EC2
Amazon C2S
on-premise
480 cores, 1.6TB ram, 30TB storage
monitor admin
Trinity
mgmt console
monitor admin
Map
service
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
8 cores
28 GB ram
400 GB ssd
1 1 11 1 2 2 3 4 3 65 7
1 1 1 1 1 12 2 2 3 4
Deployment Portability
Trinity ArcGIS
Enterprise
amongst public cloud providers, private cloud providers & on-premise environments
Source
ingestion
Gateway Real-Time
analytic
Spatiotemporal
store
Batch
analytic

28. Amazon EC2
Microsoft Azure
504 cores, 1.7TB ram, 30TB storage
public agents
admin
masters
private agents
proxy proxy proxy
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
dcos-iot-demo
https://github.com/amollenkopf/dcos-iot-demo

29. PHYSICAL (x86) VIRTUAL HYPERSCALE
SERVER
VIRTUAL
MACHINE
UNIT OF
INTERACTION
● ERP, CRM, Productivity,
Mail & Web Server
● Linux, Windows
● ERP, CRM, Productivity,
Mail & Web Server
● Hypervisor + guest OS
???DATACENTER
new form factor for
developing and running apps
● Internet of Things, Big Data,
Mobile Apps
● Containers + microServices
DEFINITIVE
APPS AND OS
A LITTLE HISTORY

30. A LITTLE HISTORY
Kernel
Operating System
…
=

31. =
Distributed
Systems Kernel
Data Center
Operating System
scheduler & resource managerpublic agents
proxy proxy
private agents
M
M
M
=

32. Microsoft Azure via Azure Resource Manager (ARM) templates
Amazon EC2 via CloudFormation templates
Amazon C2S via CloudFormation templates (offline)
on-premise via IT Administrators
Step 1: Provision Resources
specific to the selected provider
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
public agents
admin
masters
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
private agents
2 cores
7 GB ram
200 GB ssd
boot node

33. Step 1: Provision Resources
via Azure Resource Manager (ARM) templates

34. Microsoft Azure
Amazon EC2
Amazon C2S
on-premise
Step 2: Install DC/OS
install DC/OS powered by Apache Mesos
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
public agents
admin
masters
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
private agents
2 cores
7 GB ram
200 GB ssd
boot node

35. Microsoft Azure
Amazon EC2
Amazon C2S
on-premise
Step 2: Install DC/OS
install DC/OS powered by Apache Mesos
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
public agents
admin
masters
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
private agents
boot node
2 cores
7 GB ram
200 GB ssd

36. Microsoft Azure
Amazon EC2
Amazon C2S
on-premise
Step 2: Install DC/OS
install DC/OS powered by Apache Mesos
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
public agents
admin
masters
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
private agents
boot node
2 cores
7 GB ram
200 GB ssd

37. Microsoft Azure
Amazon EC2
Amazon C2S
on-premise
Step 2: Install DC/OS
install DC/OS powered by Apache Mesos
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
public agents
admin
masters
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
8 cores
28 GB ram
200 GB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
private agents
boot node
2 cores
7 GB ram
200 GB ssd

38. Microsoft Azure
Amazon EC2
Amazon C2S
on-premise
Step 2: Install DC/OS
install DC/OS powered by Apache Mesos
504 cores, 1.7TB ram, 30TB storage
proxy proxy proxy
public agents
admin
masters
private agents

40. Microsoft Azure
Amazon EC2
Amazon C2S
on-premise
Step 3: Install Services & Applications
install Kafka via Mesosphere Universe & deploy brokers
504 cores, 1.7TB ram, 30TB storage
public agents
admin
masters
private agents
proxy proxy proxy
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd

54. Step 3: Install Services & Applications
install Kafka via Mesosphere Universe, verifying brokers are running via DC/OS CLI

55. Microsoft Azure
Amazon EC2
Amazon C2S
on-premise
Step 3: Install Services & Applications
deploy customized Elasticsearch via Docker using Marathon (long-running services)
504 cores, 1.7TB ram, 30TB storage
public agents
admin
masters
private agents
proxy proxy proxy
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd

56. Microsoft Azure
Amazon EC2
Amazon C2S
on-premise
Step 3: Install Services & Applications
deploy customized reactive webapp via Docker using Marathon (long-running services)
504 cores, 1.7TB ram, 30TB storage
public agents
admin
masters
private agents
proxy proxy proxy
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd

57. Microsoft Azure
Amazon EC2
Amazon C2S
on-premise
Step 3: Install Services & Applications
deploy customized Spark via Docker using Marathon (long-running services)
504 cores, 1.7TB ram, 30TB storage
public agents
admin
masters
private agents
proxy proxy proxy
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd

58. Microsoft Azure
Amazon EC2
Amazon C2S
on-premise
Step 3: Install Services & Applications
deploy source ingestion tasks via Docker using Marathon (long-running services)
504 cores, 1.7TB ram, 30TB storage
public agents
admin
masters
private agents
proxy proxy proxy
16 cores
56 GB ram
1 TB ssd
16 cores
56 GB ram
1 TB ssd

59. • ‘dcos-iot-demo’ repo, for more information on deployment portability & the sample IoT app:
• ‘Integrating IoT & ArcGIS’ Esri User Conference pre-conference seminar content:
additional resources
Enabling Scalable IoT Applications
https://github.com/amollenkopf/dcos-iot-demo
https://github.com/Esri/integrating-iot-arcgis

60. Questions / Feedback?
Adam Mollenkopf
Real-Time & Big Data GIS Capability Lead, Esri
amollenkopf@esri.com
@amollenkopf
https://github.com/amollenkopf/dcos-iot-demo
https://github.com/Esri/integrating-iot-arcgis